Global Flood Evacuation Big Data System: From Local to Worldwide Planning

Project Overview

We developed a comprehensive, scalable evacuation planning system to address global flood scenarios. The project evolved through three phases, starting with a local focus on the Netherlands and scaling up to worldwide coverage, incorporating big data technologies for real-time processing and analysis.

Key Technologies

• Apache Spark: For distributed data processing and analysis
• Amazon Web Services (AWS): For scalable cloud computing resources
• Apache Kafka: For real-time data streaming and processing
• H3 Geospatial Indexing: For efficient geospatial calculations
• OpenStreetMap Data: For geographical and population information
• Parquet and ORC File Formats: For efficient big data storage and retrieval

Development Process

1. Phase 1: Netherlands Evacuation Planning
   • Implemented initial evacuation algorithm using Apache Spark
   • Processed OpenStreetMap data for the Netherlands
   • Utilized H3 indexing for geospatial calculations
   • Achieved efficient data processing for a single country
2. Phase 2: Scaling to Global Evacuation Planning
   • Migrated to AWS for increased computational power
   • Optimized data processing for planetary-scale datasets
   • Implemented precomputation techniques for elevation data
   • Achieved significant performance improvements, reducing processing time from hours to minutes
3. Phase 3: Real-time Evacuation Updates
   • Integrated Apache Kafka for real-time data streaming
   • Developed a stateful stream processing application
   • Implemented time-windowed aggregations for dynamic updates
   • Created a system capable of handling continuous, global-scale updates

Key Innovations

1. Planetary Elevation Precomputation: Significantly reduced processing time by precomputing average elevations for H3 indices globally.

2. Scalable Cluster Configuration: Optimized AWS cluster configurations for both precomputed and non-precomputed scenarios, balancing performance and cost.

3. Real-time Update System: Developed a Kafka-based system capable of processing global-scale evacuation updates in real-time, with configurable time windows.

Performance Highlights

• Reduced global evacuation plan computation from hours to under 5 minutes
• Achieved real-time updates for global refugee movements
• Optimized cost-efficiency, reducing AWS expenses while maintaining performance

Future Work

Potential areas for future development include:

• Integration with real-time weather and flood prediction models
• Development of a user-facing application for public evacuation guidance
• Further optimization of data processing pipelines for even faster global-scale computations

Detailed Reports

For in-depth technical information and project progression, please refer to our series of reports:

• Netherlands Evacuation Planning
• Global-Scale Evacuation System
• Real-Time Evacuation Updates